A new approach to minimization of the surface roughness and cutting force via fuzzy TOPSIS, multi-objective grey design and RSA

被引:106
作者
Gok, Arif [1 ]
机构
[1] Amasya Univ, Fac Technol, Dept Mech Engn, Amasya, Turkey
关键词
Grey relational analysis; Fuzzy TOPSIS; Response surface analysis; Optimization; Prediction model; TAGUCHI METHOD; TURNING OPERATIONS; PARAMETERS; OPTIMIZATION; FINISH; EDM;
D O I
10.1016/j.measurement.2015.03.037
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
Surface roughness affects the strength of parts during contact and working performance. Therefore, generating optimum surface roughness values are crucial to obtain high productivity in the manufacturing of turning geometries. This study presents a new method of choosing optimal cutting parameters. The first aim of this study is to investigate turning of ductile iron using fuzzy TOPSIS and grey relational analysis of optimum cutting parameter values. The second aim of the study is to determine using response surface analysis of mathematical model depending on cutting parameters of average surface roughness, maximum roughness, and main cutting force and feed force in turning. The adequacy of the developed mathematical model is proved by ANOVA. The results indicate that the depth of cut was the dominant property on the surface roughness and cutting forces. (C) 2015 Elsevier Ltd. All rights reserved.
引用
收藏
页码:100 / 109
页数:10
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